code: def test_1m_1cf(metric_fn):
      target = MetricFrame(
          metrics=metric_fn,
          y_true=y_t,
          y_pred=y_p,
          sensitive_features=g_2,  # Unused here
          control_features=g_1,
      )
      assert target._user_supplied_callable is True
  
      mask_a = g_1 == "aa"
      mask_b = g_1 == "ba"
      exp_metric_a = metric_fn(y_t[mask_a], y_p[mask_a])
      exp_metric_b = metric_fn(y_t[mask_b], y_p[mask_b])
  
      # User visible features
      assert isinstance(target.overall, pd.Series)
      assert len(target.overall) == 2
      assert target.overall["aa"] == exp_metric_a
      assert target.overall["ba"] == exp_metric_b
  
file_path: fairlearn/test/unit/metrics/test_metricframe_overall.py
imports: import numpy
  import pandas
  import pytest
  import sklearn.metrics
  from fairlearn.metrics import MetricFrame
  from .data_for_test import g_1, g_2, g_3, s_w, y_p, y_t
label_desc: Use image node_id 6 for calling a global function with example usage: test_1m_1cf(metric_fn) without return types